itrogen oxides (NOx) emissions play an important role in air quality, the nitrogen cycle, and as precursor for climate gasses. The most important sources of NOx emissions are fossil fuel burning (industry and traffic) and the release from soil.
With the inversion algorithm DECSO (Daily Emissions Constrained by Satellite Observations) we derive quantitative NOx emissions on a 5 to 20 km resolution from TROPOMI (on Sentinel 5p) observations of NO2, taking advantage of the fine spatial resolution (5 x 3.5 km) of the TROPOMI instrument. The emissions are split into 3 categories: fossil-fuel, soil and maritime emissions using detailed land use information and signatures of the seasonal cycle in the emissions.
DECSO is a full inversion algorithm based on data assimilation of satellite observation and the Chemical-transport model CHIMERE. For the data assimilation a Kalman Filter technique is used. For the inversion no apriori information of the NOx emissions is needed and for this reason new sources can be detected.
To assess the quality of satellite-derived NOx emissions, they are compared to satellite-derived emissions calculated with the divergence method and compared to NOx emissions of various bottom-up inventories. The divergence method has been applied on TROPOMI data for a 3 month period to derive average emissions over Europe. For bottom-up emissions we selected both the CAMS (Copernicus Atmosphere Monitoring Service) regional anthropogenic emission database and the regional emission inventory HERMES (High-Elective Resolution Modelling Emission System) for Catalonia for the intercomparison. The analysis has been done for regional totals but also focussing on specific cities and factories. Detailed results will be shown, including the spatial and temporal variation per emission category. The intercomparison of DECSO with bottom-up inventories show good agreement for regional emission totals and its spatial distribution, but at a city-scale or focussing on individual sources (factories or power plants) interesting differences are found.

Crude oil production activities and associated petroleum gas (APG) flaring are responsible for significant air polluting and greenhouse gas (GHG) emissions and have negative effects on the environment and climate. In Russia, one of the world's major oil producers, APG flaring remains a routine practice despite regulatory policies. We present the first analysis of nitrogen oxide and methane emissions over Tas-Yuryakh and Talakan oil fields in Sakha Republic (Eastern Siberia, Russia) using multi-satellite observations.
Satellite-based TROPOMI (TROPOspheric Monitoring Instrument) nitrogen dioxide (NO2) mean fields show local NO2 enhancements corresponding to the locations of gas flares detected from Sentinel 2 imagery and VIIRS (Visible Infrared Imaging Radiometer Suite) fire data. We derive the annual nitrogen oxide (NOx = NO2+NO) emissions from TROPOMI NO2 observations using an exponentially-modified Gaussian model. We obtain NOx emissions up to 1.34 mol/s (in 2019) in Tas-Yuryakh, where persistent production APG flaring is detected, and about 0.6 mol/s in Talakan, where oil production is three times larger than in Tas-Yuryakh but gas flaring is employed only occasionally. In 2019 we observe a new flaring site in Tas-Yuryakh from the NO2 mean fields, corresponding to an increase in the environmental fees paid by the companies to the local budgets. Assuming that all NOx emissions are associated with APG flaring, the volume of gas flared for 2019 is estimated at 1.25 ± 0.48 billion cubic metres (bcm) in Tas-Yuryakh and 0.5 ± 0.2 bcm in Talakan.
Furthermore, we find a clear methane (CH4) anomaly of about 30 ppb from the TROPOMI XCH4 mean fields near Talakan oil field. We estimate mean CH4 emissions of about 28 tons/h from individual TROPOMI XCH4 plumes using the cross-sectional flux method. CH4 enhancements over other oil and gas fields in the area are also detected.
The estimated satellite-based NOx and CH4 emissions are higher than the inventories, which are expected to underestimate the contribution from the oil and gas industry and are generally available with several years of delay. TROPOMI NO2 and CH4 observations demonstrate their capability in identifying emission sources from space with unprecedented detail. The results show how satellite observations can support environmental authorities in monitoring the emissions from the oil and gas industry and the commitment of oil companies in reducing APG flaring.

Precise knowledge of the location and height of the volcanic sulfur dioxide (SO ) plume is essential for accurate determination of SO emitted by volcanic eruptions. So far, UV based SO plume height retrieval algorithms are very time-consuming and therefore not suitable for near-real-time applications like aviation control, although the SO LH is essential for accurate determination of SO2 emitted by volcanic eruptions.

We have therefore developed the Full-Physics Inverse Learning Machine (FP_ILM) algorithm using a combined principal components analysis (PCA) and neural network approach (NN) to extract the information about the volcanic SO LH from high-resolution UV backscatter measurement of TROPOMI aboard Sentinel-5 Precursor. The FP_ILM approach enables for the first time to extract the SO LH information in a matter of seconds for an entire S5P orbit and is thus applicable in NRT applications.
In this presentation, we will present the FP-ILM algorithm and show results of recent volcanic eruptions.

The SO layer height product is developed in the framework of the SO Layer Height (S5P+I: SO2 LH) project, which is part of ESA Sentinel-5p+ Innovation project (S5P+I). The S5P+I project aims to develop novel scientific and operational products to exploit
the potential of the S5P/TROPOMI capabilities. The S5P+I: SO LH project is dedicated to the generation of an SO LH product and its extensive verification with collocated ground- and space-born measurements.

Usually, horizontal homogenous atmospheric properties are assumed for the analysis of satellite observations of atmospheric trace gases. While for most cases, this simplification causes only small to moderate errors, for the observation of volcanic plumes this assumption can lead to very large errors. 3D effects can become especially important for satellite observations with high spatial resolution like TROPOMI on S5P. While with TROPOMI many narrow volcanic plumes with low trace gas concentrations can be detected for the first time, 3D effects for these observations have to be addressed.
Three different 3D effects are investigated in this study: a) geometric light path effects: the light path from the sun to the surface and that from the surface to the satellite might not both cross the volcanic plume; b) effects of horizontal light paths: light scattered into the FOV might originate from regions outside the volcanic plume and thus lead to a decrease of the absorption signal; c) saturation effects (for SO2): for narrow plumes the SO2 absorption signal can be strongly suppressed because most of the backscattered light is absorbed by SO2 itself.
We investigate all three effects with the 3D Monte-Carlo radiative transfer model TRACY-2. We consider typical volcanic plumes and make simulations for observations directly above the volcano as well as in the horizontally oriented plume far away from the volcano. In order to quantify the associated errors we compare the results of the 3D simulations with those from simple 1D simulations.
We find that especially for narrow volcanic plumes with extensions of only a few hundred meters to a few kilometers, the number of molecules in the plume can be strongly underestimated (>50%) for sensors with small ground pixel sizes. These findings are also relevant for other narrow plumes like from power plant emissions. For narrow plumes with high SO2 concentrations, the underestimation can become close to 100%.
We also investigate 3D effects for ground based observations.
Finally, we give recommendations on how to best address 3D effects for the analysis of satellite observations of volcanic plumes.

The Cumbre Vieja volcano on La Palma in the Canary Islands erupted for the first time in 50 years on 19 September 2021 causing widespread devastation on the island. The most prominent impact on the atmosphere was in terms of almost continuous daily emissions of sulphur dioxide (SO2) for several weeks following the initial eruption. The relatively high levels of SO2 and subsequent sulphate aerosol formation were observed across northern Africa, Europe, where the highest concentrations were generally well above the surface in the free troposphere, and the Atlantic Ocean, where a mixture of sulphate and desert dust aerosols led to episodes of degraded air quality in Puerto Rico and other Caribbean countries. Analyses and forecasts from the Copernicus Atmosphere Monitoring Service (CAMS), implemented by the European Centre for Medium-Range Weather Forecasts (ECMWF) with funding from the European Union, are based on the assimilation of total column SO2 observations from the TROPOMI and GOME-2 satellite instruments. In the current operational CAMS system an initial injection height of SO2 in an atmospheric layer at 500 hPa is assumed for volcanic eruptions and the assimilated SO2 can influence sulphate aerosol through interactions between the gas-phase and aerosol chemistry schemes used in the model. Observed SO2 layer heights derived from TROPOMI were between 700 and 500 hPa , i.e. slightly lower than the height assumed in the CAMS operational system but, in general, the long-range transport patterns of CAMS total column SO2 forecasts were well matched with independent observations. Assimilation of the TROPOMI SO2 layer height information is being implemented in CAMS and is anticipated to lead to improved monitoring of the atmospheric impacts of volcanic eruptions in future. We present an overview of the performance of the CAMS SO2 and sulphate aerosol analyses and forecasts in relation to the Cumbre Vieja eruption, focussing on long-range transport across Europe and the Atlantic Ocean and initial evaluation of the CAMS forecasts against independent ground-based and in situ measurements.

The Infrared Atmospheric Sounding Interferometer (IASI) is a hyperspectral sensor onboard the Metop satellite platforms. The first instrument was launched in 2006, with data first becoming available in the middle in 2007, and two more instruments have since been launched. Within the instrument’s spectral range there is sensitivity to sulphur dioxide (SO2) and volcanic ash. Retrieval schemes which exploit the sensitivity within the IASI spectra to SO2 have been developed by the Earth Observation Data Group (EODG) at the University of Oxford, to detect and quantify information about these plumes. The first tool, a linear retrieval, can be used to rapidly detect SO2, facilitating its use in near real time. The second method, an iterative retrieval, is able to quantify information about the plume, namely the SO2 column amount and the height. This method also generates a comprehensive error matrix which helps to interpret the results. This information is valuable for assessing the hazard these plumes present (e.g. to aircraft), for studying trends in volcanic activity and for investigating the impacts of these plumes on the environment and climate.

The Oxford retrieval schemes have now been applied to over a decade of IASI spectra. This extensive dataset includes estimates of emissions from large eruptions, the largest being of Nabro in Eritrea which erupted in 2011; smaller eruptions and more persistent emissions from volcanic sources (e.g. Popocatepetl in Mexico and Etna in Italy); and anthropogenic emissions of SO2 (e.g. in South Africa, Russia and China). Using this dataset, it has been possible to get a daily SO2 mass for the entire time period. It has also been possible to explore the distribution of SO2 with latitude and height: important factors in determining the lifetime, extent of dispersion and the atmospheric impacts. This project aims to archive the IASI SO2 products to make then easily accessible to other researchers.